Infrastructure Engineer

• Build and scale distributed training infrastructure supporting large AI models across large GPU clusters
• Design and improve systems that increase training reliability, efficiency, and resource utilization
• Develop solutions for fault tolerance, checkpointing, recovery, and large-scale training operations
• Integrate AI models into production training pipelines with platform, orchestration, and performance engineering teams
• Diagnose and resolve issues impacting training throughput, stability, reliability, and cost efficiency
• Build tools and automation that improve the developer experience for AI researchers and engineers
• Establish best practices for training infrastructure, operational processes, and platform reliability
• Contribute to the evolution of the AI infrastructure platform as an early engineering team member

Staff AI Training Infrastructure Engineer

• Own the architecture, configuration, and ongoing administration of Linear and Airtable across Digital Enterprise Technology
• Lead rollout and scaling of new platform capabilities from initial launch through enterprise-wide adoption
• Design and build integrations, automations, and custom workflows connecting Linear, Airtable, and adjacent collaboration/productivity systems
• Develop integrations between SaaS platforms and enterprise systems
• Automate user provisioning, lifecycle management, and operational processes
• Improve operational efficiency through automation and reusable tooling
• Establish and enforce governance standards for permissions, data models, naming conventions, and usage policies
• Partner with engineering leaders, program managers, and business stakeholders to translate requirements into system configurations
• Monitor platform health, usage, and performance; troubleshoot issues and drive resolution
• Evaluate new tools and features and recommend platform strategy and roadmap
• Create documentation, training materials, and enablement resources
• Provide technical mentorship to engineers and administrators supporting these platforms

Senior Infrastructure Engineer – Collaboration

• Design, build, and operate goal-oriented AI agents that automate SRE, DevOps, and DBA workflows
• Build agents for incident investigation and remediation, infrastructure provisioning, deployment orchestration, database operations, and capacity management
• Design agent loops with planning, reasoning, tool use, error recovery, and human-in-the-loop escalation
• Integrate agents with Kubernetes, Terraform, AWS, GCP, Aliyun, monitoring platforms, databases, and CI/CD pipelines
• Define metrics and build evaluation frameworks for agent effectiveness
• Partner with SRE, DevOps, and platform engineering teams to identify workflows for automation
• Contribute to the technical vision for AI-driven infrastructure operations

Infrastructure Engineer jobs in Washington

Staff AI Training Infrastructure Engineer

Senior Infrastructure Engineer – Collaboration

Software Engineer, Infrastructure AI